视觉模拟优化算法研究

Research on Visual Simulation Optimization Algorithm

本文提出一种新的元启发优化算法即视觉模拟优化算法,其是通过模拟生物的视觉系统来完成搜索的新型算法。视觉模拟优化算法与遗传算法、差分进化算法、粒子群算法、模拟退火算法以及人工蜂群算法在10个基准测试函数上进行对比研究,结果显示该算法在所有测试函数中优化效果均优于其他算法。为了进一步检验视觉模拟优化算法的有效性,用其求解非线性方程组,结果显示该算法有效且优于其他对比算法。

This paper proposes a new meta heuristic optimization algorithm, namely visual simulation optimization algorithm, which is a new algorithm to complete the search by simulating the biological visual system. Visual simulation optimization algorithm is compared with genetic algorithm, differential evolution algorithm, particle swarm optimization algorithm, simulated annealing algorithm and artificial bee colony algorithm on 10 benchmark functions. The results show that the optimization effect of this algorithm is better than other algorithms in all test functions. In order to further test the effectiveness of visual simulation optimization algorithm, it is used to solve nonlinear equations. The results show that the algorithm is effective and better than other comparison algorithms.